import torch
from diffusers import DiffusionPipeline
from diffusers.utils import load_image
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("fofr/flux-kontext-dev-jpeg-compression-fix-lora")
prompt = "fix the jpeg compression"
input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")
image = pipe(image=input_image, prompt=prompt).images[0]Fix JPEG artifacts compression lora
- Prompt
- fix the jpeg compression
- Prompt
- fix the jpeg compression
About this LoRA
This is a LoRA for the FLUX.1-kontext-dev image-to-image model. It can be used with diffusers or ComfyUI.
It was trained on Replicate.
Trigger words
You should use fix the jpeg compression to trigger the image generation.
Contribute your own examples
You can use the community tab to add images that show off what you’ve made with this LoRA
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Model tree for fofr/flux-kontext-dev-jpeg-compression-fix-lora
Base model
black-forest-labs/FLUX.1-Kontext-dev